恭喜Taiwan R User Group 三歲了
2015-11-16
首先
據說
今天有殘酷擂台
所以在這特別的日子
當然要講一些 有的沒有的有趣的主題
DQMSL
是什麼？可以吃嗎？
DQMSL = 勇者鬥惡龍怪物仙境
當初看到這個遊戲
身為骨灰級的玩家眼淚都要掉下來了啊
不知荒廢了多少的青春
既然叫做怪物仙境
就是有很多怪物的意思
為了這次的活動
我就稍微爬了一下怪物的資料
Load libraries
library(rvest) library(stringr) library(data.table) library(googleVis) library(ca) library(proxy)
Get urls
ranking_pages = read_html("http://dqmsl-search.net/ranking/allsbjstatus?hide=&hides=,star1,star2,star3,star4")
urls_xpath = "/html/body/div[@class='mainh']/div[@class='mainc']/div[@class='ccol']/div[@class='mbox'][2]/div[@class='mboxb']/div/div[@class='innnerHideDiv']/div/div/a"
base_url = "http://dqmsl-search.net"
monster_urls = ranking_pages %>%
html_nodes(xpath = urls_xpath) %>%
html_attr(name = "href") %>%
unique() %>%
(function(x) {paste0(base_url, x, sep = "")})
monster_urls[1:3]
## [1] "http://dqmsl-search.net/monster/detail?no=501" ## [2] "http://dqmsl-search.net/monster/detail?no=521" ## [3] "http://dqmsl-search.net/monster/detail?no=543"
ETL is omitted.
Preprocessing
monsters = fread("data/monsters.csv")
character_cols = c("id", "name", "rank", "system", "type")
numeric_cols = names(monsters)[!names(monsters) %in% character_cols]
monsters[, c(numeric_cols) := lapply(.SD, as.numeric), .SDcols = numeric_cols]
monsters[, total := hp + mp + str + def + agi + int]
monsters[, icon := sprintf('<img src="img/icon/%s.gif" alt="%s" width="40">',
str_pad(id, width = 6, pad = "0"), id, name)]
monsters[, name := sprintf("<a href='http://dqmsl-search.net/monster/detail?no=%s'>%s</a>",
id, name)]
monsters[, `:=`(like_percent = like / view * 100,
hate_percent = hate / view * 100)]
monsters = monsters[order(total, decreasing = TRUE),]
Monsters' Data
mtable = gvisTable(monsters, options = list(page = "enable",
pageSize = 5))
print(mtable, "chart")
Plot categorical data with barchart
print_bar = function(dt, colname, height = 400, width = 900) {
percent = dt[, .(percent = .N), by = colname][
, percent := percent / sum(percent) * 100]
print(gvisBarChart(percent, options = list(height = height, width = width)),
"chart")
}
Rank distribution
print_bar(monsters, "rank")
System distribution
print_bar(monsters, "system")
Type distribution
print_bar(monsters, "type")
System vs Type
system_type = table(monsters$system, monsters$type) system_type
## ## 万能 回復 攻撃 特殊 補助 防御 魔法 ## 悪魔系 5 3 32 10 17 3 52 ## 物質系 0 4 36 7 19 26 10 ## ドラゴン系 2 2 64 1 4 10 1 ## スライム系 6 11 24 10 5 11 3 ## ？？？系 5 1 21 12 0 0 14 ## ゾンビ系 3 2 27 1 7 4 6 ## 自然系 7 6 27 5 19 20 7 ## 転生系 0 0 0 35 0 0 0 ## 魔獣系 5 3 70 6 21 10 7
Stacked barchart
system_type_dt = as.data.table(round(prop.table(system_type, margin = 1) * 100, 2))
setnames(system_type_dt, names(system_type_dt), c("system", "type", "count"))
system_type_dt = dcast(system_type_dt, system ~ type, value.var = "count")
yvar = names(system_type_dt)[!names(system_type_dt) %in% "system"]
print(gvisBarChart(system_type_dt, xvar = "system", yvar = yvar,
options = list(isStacked = TRUE, height = 300, width = 900)), "chart")
Correspondence analysis
cafit = ca(system_type)
ca_dt = rbind(data.table(Dim1 = cafit$rowcoord[, 1],
system = cafit$rowcoord[, 2],
system.html.tooltip = rownames(system_type),
type = rep(NA, nrow(system_type)),
type.html.tooltip = rep(NA, nrow(system_type))),
data.table(Dim1 = cafit$colcoord[, 1],
system = rep(NA, ncol(system_type)),
system.html.tooltip = rep(NA, ncol(system_type)),
type = cafit$colcoord[, 2],
type.html.tooltip = colnames(system_type)))
tick_str = "{'ticks': [-5, -4, -3, -2, -1, 0, 1, 2] }"
ca_plot = gvisScatterChart(ca_dt, options = list(width = 500, height = 500,
hAxis = tick_str, vAxis = tick_str))
Correspondence analysis - 2
The total variance of the data matrix is measured by the inertia, which ressembles a chi-square statistic but is calculated on relative observed and expected frequencies.
cafit
## ## Principal inertias (eigenvalues): ## 1 2 3 4 5 6 ## Value 0.405606 0.186753 0.087494 0.044128 0.013726 0.005737 ## Percentage 54.56% 25.12% 11.77% 5.94% 1.85% 0.77% ## ## ## Rows: ## 悪魔系 物質系 ドラゴン系 スライム系 ？？？系 ゾンビ系 ## Mass 0.167353 0.139918 0.115226 0.096022 0.072702 0.068587 ## ChiDist 0.870226 0.533945 0.757989 0.669843 0.723305 0.376019 ## Inertia 0.126735 0.039890 0.066203 0.043084 0.038036 0.009698 ## Dim. 1 0.005581 0.303270 0.624426 -0.109549 -0.626504 0.492531 ## Dim. 2 -2.005154 0.456370 0.916871 0.717588 -0.951892 0.032618 ## 自然系 転生系 魔獣系 ## Mass 0.124829 0.048011 0.167353 ## ChiDist 0.525387 2.716489 0.430770 ## Inertia 0.034457 0.354288 0.031054 ## Dim. 1 0.338404 -4.218845 0.402011 ## Dim. 2 0.425708 0.824756 0.426592 ## ## ## Columns: ## 万能 回復 攻撃 特殊 補助 防御 魔法 ## Mass 0.045267 0.043896 0.412894 0.119342 0.126200 0.115226 0.137174 ## ChiDist 0.668747 0.912812 0.447466 1.718554 0.541708 0.752207 1.043109 ## Inertia 0.020245 0.036575 0.082672 0.352467 0.037033 0.065197 0.149256 ## Dim. 1 0.159083 0.238895 0.447837 -2.686864 0.445905 0.480385 0.046881 ## Dim. 2 -0.240881 0.613545 0.387561 0.356418 -0.022284 0.986840 -2.401930
Correspondence analysis - 3
print(ca_plot, "chart")
Weight
print(ftable(rank ~ weight, data = monsters))
## rank A B C D E F S SS ## weight ## 2 0 0 0 71 38 15 0 0 ## 3 0 0 80 0 0 0 0 0 ## 6 0 112 0 0 0 0 0 0 ## 9 171 0 0 0 0 0 0 0 ## 14 0 0 0 0 0 0 61 0 ## 18 0 0 0 0 0 0 110 0 ## 23 0 0 0 0 0 0 9 0 ## 27 0 0 0 0 0 0 0 53 ## 32 0 0 0 0 0 0 0 9
Classical Multidimensional scaling
Here we choose SS monsters to find distance of monsters via hp, mp, str, def, agi and int.
body_cols = c("hp", "mp", "str", "def", "agi", "int")
scaled_body_cols = paste0("scaled_", body_cols)
ss = copy(monsters[rank %in% c("SS"), ])
ss[, icon := str_replace(icon, 'width=\"40\"', 'width=\"120\"')]
ss[, c(scaled_body_cols) := lapply(.SD, scale), .SDcols = body_cols]
ss_dist = dist(ss[, scaled_body_cols, with = FALSE])
fit = cmdscale(ss_dist, eig = TRUE, k=2)
plot_dt = data.table(Dim1 = fit$points[,1],
Dim2 = fit$points[,2],
Dim2.html.tooltip = ss$icon)
plot_out = gvisScatterChart(plot_dt, options=list(tooltip="{isHtml:'true'}",
width = 500, height = 500,
legend = '{"position": "none"}'))
Classical Multidimensional scaling - 2
GOF measures the goodness of fit of Multidimensional scaling
g.i = (sum{j=1..k} λ[j]) / (sum{j=1..n} T.i(λ[j])), where:
- λ[j] are the eigenvalues (sorted in decreasing order)
- T.1(v) = abs(v)
- T.2(v) = max(v, 0)
fit$GOF
## [1] 0.667616 0.667616
Classical Multidimensional scaling - 3
print(plot_out, "chart")
Compute mean for each type
ss_type_mean = ss[, lapply(.SD, mean),
by = c("type"),
.SDcols = body_cols]
ss_type_mean = dcast(melt(ss_type_mean, id.vars = "type"), variable ~ type)
plot_out = gvisLineChart(ss_type_mean, xvar = "variable",
options = list(height = 300, width = 800))
print(plot_out, "chart")
Skills of monsters
Skills of monsters can be found in this page.
skills = fread("data/skills.csv")
skills[, skill_mp := str_replace_all(skill, "^.*\\(消費MP:|\\)$", "")]
# skills[, skillasd := str_replace_all(skill, "\\(消費MP:.*\\)|\\W", "")]
skills = suppressWarnings(merge(skills,
monsters[, .(monster = gsub("<a href=\\'.*\\'>|</a>", "",
monsters$name), rank, name, icon)],
by = "monster", all.x = TRUE, all.y = FALSE))
stable = gvisTable(skills, options = list(page = "enable",
pageSize = 5))
Skills Table
print(stable, "chart")
Skills type
print_bar(skills, "skill_type")
Most common skills
skill_count = skills[, .(count = .N), by = "skill"][order(-count)]
sctable = gvisTable(skill_count, options = list(page = "enable",
pageSize = 10))
print(sctable, "chart")
Multidimensional scaling via skill
ss_skills = copy(skills[rank %in% c("SS"),])
monster_skill = table(ss_skills$monster, ss_skills$skill)
skills_dist = dist(monster_skill, method = "jaccard")
ss_skills_dist = dist(monster_skill, method = "jaccard")
fit = cmdscale(ss_skills_dist, eig = TRUE, k=2)
plot_dt = data.table(Dim1 = fit$points[,1],
Dim2 = fit$points[,2],
Dim2.html.tooltip = ss$icon)
plot_out = gvisScatterChart(plot_dt, options=list(tooltip="{isHtml:'true'}",
width = 500, height = 500,
legend = '{"position": "none"}'))
Multidimensional scaling via skill - 2
The GOF is only around 0.11.
fit$GOF
## [1] 0.1109962 0.1113186
Multidimensional scaling via skill - 3
print(plot_out, "chart")
Correspondence analysis via skill
ss_skills = copy(skills[rank %in% c("SS"),])
monster_skill = table(ss_skills$monster, ss_skills$skill)
cafit = ca(monster_skill)
ca_dt = rbind(data.table(Dim1 = cafit$rowcoord[, 1],
system = cafit$rowcoord[, 2],
system.html.tooltip = rownames(monster_skill),
type = rep(NA, nrow(monster_skill)),
type.html.tooltip = rep(NA, nrow(monster_skill))),
data.table(Dim1 = cafit$colcoord[, 1],
system = rep(NA, ncol(monster_skill)),
system.html.tooltip = rep(NA, ncol(monster_skill)),
type = cafit$colcoord[, 2],
type.html.tooltip = colnames(monster_skill)))
tick_str = "{'ticks': [-5, -4, -3, -2, -1, 0, 1, 2] }"
ca_plot = gvisScatterChart(ca_dt, options = list(width = 500, height = 500,
hAxis = tick_str, vAxis = tick_str))
Correspondence analysis via skill - 2
The principal inertias is very low.
cafit
## ## Principal inertias (eigenvalues): ## 1 2 3 4 5 6 7 8 9 10 ## Value 1 1 1 1 1 1 1 1 1 1 ## Percentage 2.67% 2.67% 2.67% 2.67% 2.67% 2.67% 2.67% 2.67% 2.67% 2.67% ## 11 12 13 14 15 16 17 18 19 ## Value 1 1 1 1 1 1 0.977611 0.968068 0.966021 ## Percentage 2.67% 2.67% 2.67% 2.67% 2.67% 2.67% 2.61% 2.58% 2.58% ## 20 21 22 23 24 25 26 ## Value 0.940911 0.891581 0.853553 0.853553 0.830871 0.809353 0.804418 ## Percentage 2.51% 2.38% 2.28% 2.28% 2.22% 2.16% 2.15% ## 27 28 29 30 31 32 33 34 ## Value 0.766277 0.75 0.714202 0.694889 0.686389 0.609504 0.5 0.5 ## Percentage 2.04% 2% 1.9% 1.85% 1.83% 1.63% 1.33% 1.33% ## 35 36 37 38 39 40 41 42 43 ## Value 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.390496 ## Percentage 1.33% 1.33% 1.33% 1.33% 1.33% 1.33% 1.33% 1.33% 1.04% ## 44 45 46 47 48 49 50 51 ## Value 0.313611 0.305111 0.285798 0.25 0.25 0.25 0.233723 0.195582 ## Percentage 0.84% 0.81% 0.76% 0.67% 0.67% 0.67% 0.62% 0.52% ## 52 53 54 55 56 57 58 ## Value 0.190647 0.169129 0.146447 0.146447 0.108419 0.059089 0.033979 ## Percentage 0.51% 0.45% 0.39% 0.39% 0.29% 0.16% 0.09% ## 59 60 61 ## Value 0.031932 0.022389 0 ## Percentage 0.09% 0.06% 0% ## ## ## Rows: ## カンダタ デンガー マガルギ ゲリュオン ソードイド ハヌマーン ## Mass 0.016393 0.016393 0.016393 0.016393 0.016393 0.016393 ## ChiDist 7.745967 6.689544 4.677072 4.097764 6.689544 6.093029 ## Inertia 0.983607 0.733607 0.358607 0.275273 0.733607 0.608607 ## Dim. 1 7.745967 -0.129099 -0.129099 -0.129099 -0.129099 -0.129099 ## Dim. 2 0.000000 -0.112890 -0.658755 0.237590 -0.112890 -0.658755 ## ヘルバオム メカバーン キングヒドラ ゴッドバロン セルゲイナス ## Mass 0.016393 0.016393 0.016393 0.016393 0.016393 ## ChiDist 7.745967 6.689544 6.298148 6.298148 3.907258 ## Inertia 0.983607 0.733607 0.650273 0.650273 0.250273 ## Dim. 1 -0.129099 -0.129099 -0.129099 -0.129099 -0.129099 ## Dim. 2 -1.840257 -0.658755 -0.137507 -0.112890 0.237590 ## デスアラウネ デスカイザー ライオネック ヴァルハラー てんのもんばん ## Mass 0.008197 0.016393 0.016393 0.016393 0.016393 ## ChiDist 7.745967 5.966574 4.677072 5.431390 5.966574 ## Inertia 0.491803 0.583607 0.358607 0.483607 0.583607 ## Dim. 1 -0.129099 -0.129099 -0.129099 -0.129099 -0.129099 ## Dim. 2 0.257814 -0.658755 -0.658755 -0.112890 0.237590 ## キラーマジンガ グランシーザー デスプリースト デーモンキング ## Mass 0.016393 0.016393 0.016393 0.016393 ## ChiDist 4.941322 6.093029 6.298148 3.907258 ## Inertia 0.400273 0.608607 0.650273 0.250273 ## Dim. 1 -0.129099 -0.129099 -0.129099 -0.129099 ## Dim. 2 -0.112890 0.237590 -0.658755 -0.658755 ## ドラゴンガイア バラモスゾンビ バラモスブロス ブラッドナイト ## Mass 0.016393 0.016393 0.016393 0.016393 ## ChiDist 7.745967 5.431390 5.966574 5.431390 ## Inertia 0.983607 0.483607 0.583607 0.483607 ## Dim. 1 -0.129099 -0.129099 -0.129099 -0.129099 ## Dim. 2 4.299633 -0.658755 -0.658755 -0.112890 ## ヘビーマジンガ ヘルヴィーナス メタルカイザー れんごくまちょう ## Mass 0.016393 0.016393 0.016393 0.016393 ## ChiDist 6.689544 6.298148 5.431390 6.298148 ## Inertia 0.733607 0.650273 0.483607 0.650273 ## Dim. 1 -0.129099 -0.129099 -0.129099 -0.129099 ## Dim. 2 1.074384 0.237590 -0.658755 -0.137507 ## エビルエスターク オーシャンボーン クインガルハート ## Mass 0.016393 0.016393 0.016393 ## ChiDist 6.689544 3.567212 6.689544 ## Inertia 0.733607 0.208607 0.733607 ## Dim. 1 -0.129099 -0.129099 -0.129099 ## Dim. 2 1.025802 0.237590 0.237590 ## クイーンスライム ダークアラストル デビルドラグナー ## Mass 0.016393 0.016393 0.016393 ## ChiDist 3.907258 6.689544 6.093029 ## Inertia 0.250273 0.733607 0.608607 ## Dim. 1 -0.129099 -0.129099 -0.129099 ## Dim. 2 0.237590 1.025802 0.237590 ## トワイライトメア ヘルクラッシャー マジックアーマー ## Mass 0.016393 0.016393 0.016393 ## ChiDist 6.093029 5.431390 5.431390 ## Inertia 0.608607 0.483607 0.483607 ## Dim. 1 -0.129099 -0.129099 -0.129099 ## Dim. 2 0.237590 -0.112890 -0.112890 ## キングスペーディオ グラブゾンジャック ゴールデンスライム ## Mass 0.016393 0.016393 0.008197 ## ChiDist 6.093029 7.745967 7.745967 ## Inertia 0.608607 0.983607 0.491803 ## Dim. 1 -0.129099 -0.129099 -0.129099 ## Dim. 2 0.237590 1.047088 -1.276665 ## ディアノーグエース メタルスコーピオン ダイヤモンドスライム ## Mass 0.016393 0.016393 0.016393 ## ChiDist 6.689544 7.745967 4.097764 ## Inertia 0.733607 0.983607 0.275273 ## Dim. 1 -0.129099 -0.129099 -0.129099 ## Dim. 2 -1.276665 0.205313 -0.658755 ## はめつの使者 冥獣王ネルゲル 地獄の帝王エスターク ## Mass 0.016393 0.016393 0.016393 ## ChiDist 6.689544 7.745967 7.745967 ## Inertia 0.733607 0.983607 0.983607 ## Dim. 1 -0.129099 -0.129099 -0.129099 ## Dim. 2 -0.658755 0.755524 -3.128705 ## 大魔王デスタムーア 大魔王ミルドラース 怪力軍曹イボイノス 海王神 ## Mass 0.016393 0.016393 0.016393 0.016393 ## ChiDist 5.966574 4.511097 6.689544 4.941322 ## Inertia 0.583607 0.333607 0.733607 0.400273 ## Dim. 1 -0.129099 -0.129099 -0.129099 -0.129099 ## Dim. 2 -0.658755 -0.658755 1.074384 -0.112890 ## 破壊神シドー 神竜 竜王 聖地竜オリハルゴン ## Mass 0.016393 0.016393 0.016393 0.016393 ## ChiDist 5.431390 3.774917 6.298148 5.966574 ## Inertia 0.483607 0.233607 0.650273 0.583607 ## Dim. 1 -0.129099 -0.129099 -0.129099 -0.129099 ## Dim. 2 -0.658755 0.237590 -0.137507 0.237590 ## 聖天竜ミラクレア 舞踏魔プレシアンナ 邪眼皇帝アウルート ## Mass 0.016393 0.016393 0.016393 ## ChiDist 7.745967 6.689544 6.298148 ## Inertia 0.983607 0.733607 0.650273 ## Dim. 1 -0.129099 -0.129099 -0.129099 ## Dim. 2 3.153807 0.257814 0.237590 ## 闇の大魔王ゾーマ 魔剣士ピサロ 魔剣神レパルド ランプの魔王 ## Mass 0.016393 0.016393 0.016393 0.016393 ## ChiDist 7.745967 5.431390 5.431390 4.941322 ## Inertia 0.983607 0.483607 0.483607 0.400273 ## Dim. 1 -0.129099 -0.129099 -0.129099 -0.129099 ## Dim. 2 -0.811344 1.025802 1.025802 0.237590 ## 黒竜丸 ## Mass 0.016393 ## ChiDist 6.689544 ## Inertia 0.733607 ## Dim. 1 -0.129099 ## Dim. 2 -0.658755 ## ## ## Columns: ## しゃくねつ (消費MP:110) ザオリク (消費MP:120) ドルクマ (消費MP:14) ## Mass 0.024590 0.024590 0.008197 ## ChiDist 4.396969 4.396969 7.745967 ## Inertia 0.475410 0.475410 0.491803 ## Dim. 1 -0.129099 -0.129099 -0.129099 ## Dim. 2 -0.137507 -0.658755 -0.658755 ## フバーハ (消費MP:16) ダークマッシャー (消費MP:17) ## Mass 0.008197 0.008197 ## ChiDist 7.745967 7.745967 ## Inertia 0.491803 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 0.205313 -0.658755 ## しっぷうづき (消費MP:18) メラゾーマ (消費MP:19) ## Mass 0.008197 0.008197 ## ChiDist 7.745967 7.745967 ## Inertia 0.491803 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 -0.112890 -0.137507 ## におうだち (消費MP:20) ベホマズン (消費MP:200) ## Mass 0.008197 0.008197 ## ChiDist 7.745967 7.745967 ## Inertia 0.491803 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 0.237590 0.237590 ## ミラクルソード (消費MP:24) ギガデイン (消費MP:24) ## Mass 0.016393 0.032787 ## ChiDist 5.431390 3.774917 ## Inertia 0.483607 0.467213 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 -0.112890 -0.658755 ## シールドブレイク (消費MP:28) デモンズソード (消費MP:28) ## Mass 0.016393 0.008197 ## ChiDist 5.431390 7.745967 ## Inertia 0.483607 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 1.074384 1.025802 ## たたきつぶし (消費MP:28) かみくだき (消費MP:28) ## Mass 0.008197 0.032787 ## ChiDist 7.745967 3.774917 ## Inertia 0.491803 0.467213 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 1.047088 0.237590 ## ソードクラッシュ (消費MP:32) アシッドブレス (消費MP:32) ## Mass 0.008197 0.008197 ## ChiDist 7.745967 7.745967 ## Inertia 0.491803 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 1.074384 -1.840257 ## テールハンマー (消費MP:32) デスファイア (消費MP:33) ## Mass 0.008197 0.008197 ## ChiDist 7.745967 7.745967 ## Inertia 0.491803 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 0.205313 -0.658755 ## ドルモーア (消費MP:33) ボミオスブレード (消費MP:34) ## Mass 0.016393 0.024590 ## ChiDist 5.431390 4.396969 ## Inertia 0.483607 0.475410 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 -0.658755 -0.112890 ## よろいくだき (消費MP:34) サイコキャノン (消費MP:35) ## Mass 0.008197 0.008197 ## ChiDist 7.745967 7.745967 ## Inertia 0.491803 0.491803 ## Dim. 1 7.745967 -0.129099 ## Dim. 2 0.000000 -0.811344 ## マジックブレイク (消費MP:36) シャインスコール (消費MP:37) ## Mass 0.016393 0.008197 ## ChiDist 5.431390 7.745967 ## Inertia 0.483607 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 -0.112890 0.237590 ## ポイズンブレード (消費MP:38) チャームウィップ (消費MP:41) ## Mass 0.008197 0.016393 ## ChiDist 7.745967 6.689544 ## Inertia 0.491803 0.733607 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 -0.112890 0.257814 ## ダークウィップ (消費MP:41) いなずま (消費MP:41) ## Mass 0.008197 0.008197 ## ChiDist 7.745967 7.745967 ## Inertia 0.491803 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 -1.840257 -0.658755 ## いてつくはどう (消費MP:42) ジゴスラッシュ (消費MP:48) ## Mass 0.008197 0.016393 ## ChiDist 7.745967 5.431390 ## Inertia 0.491803 0.483607 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 0.237590 1.025802 ## ギガスラッシュ (消費MP:48) マホターン (消費MP:48) ## Mass 0.008197 0.008197 ## ChiDist 7.745967 7.745967 ## Inertia 0.491803 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 -0.112890 0.257814 ## ランドインパクト (消費MP:52) やみのはどう (消費MP:56) ## Mass 0.040984 0.008197 ## ChiDist 3.346640 7.745967 ## Inertia 0.459016 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 0.237590 -0.811344 ## バギクロス (消費MP:62) ジゴスパーク (消費MP:65) ## Mass 0.024590 0.016393 ## ChiDist 4.396969 5.431390 ## Inertia 0.475410 0.483607 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 0.237590 -0.658755 ## ベホマラー (消費MP:65) マヒャド (消費MP:69) べギラゴン (消費MP:74) ## Mass 0.016393 0.024590 0.016393 ## ChiDist 5.431390 4.396969 5.431390 ## Inertia 0.483607 0.475410 0.483607 ## Dim. 1 -0.129099 -0.129099 -0.129099 ## Dim. 2 0.237590 0.237590 -0.658755 ## サンダーボルト (消費MP:78) みがわり (消費MP:8) ## Mass 0.008197 0.016393 ## ChiDist 7.745967 5.431390 ## Inertia 0.491803 0.483607 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 -0.658755 -0.658755 ## イオナズン (消費MP:88) プチマダンテ (消費MP:残MP1/10) ## Mass 0.040984 0.016393 ## ChiDist 3.346640 6.689544 ## Inertia 0.459016 0.733607 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 -0.658755 -1.276665 ## ぶきみな光 (消費MP:10) 冥府の縛鎖 (消費MP:56) ## Mass 0.008197 0.008197 ## ChiDist 7.745967 7.745967 ## Inertia 0.491803 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 0.237590 0.755524 ## 大地の守り (消費MP:36) 大地の怒り (消費MP:38) 完全覚醒 (消費MP:40) ## Mass 0.008197 0.008197 0.008197 ## ChiDist 7.745967 7.745967 7.745967 ## Inertia 0.491803 0.491803 0.491803 ## Dim. 1 -0.129099 -0.129099 -0.129099 ## Dim. 2 0.237590 1.074384 -3.128705 ## 封印の霧 (消費MP:56) 帝王の一閃 (消費MP:38) ## Mass 0.008197 0.008197 ## ChiDist 7.745967 7.745967 ## Inertia 0.491803 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 -0.658755 -3.128705 ## かがやく息 (消費MP:124) 息をすいこむ (消費MP:16) ## Mass 0.016393 0.008197 ## ChiDist 5.431390 7.745967 ## Inertia 0.483607 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 -0.658755 -0.137507 ## れんごく斬り (消費MP:17) はやぶさ斬り (消費MP:21) ## Mass 0.008197 0.016393 ## ChiDist 7.745967 5.431390 ## Inertia 0.491803 0.483607 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 4.299633 -0.112890 ## マヒャド斬り (消費MP:28) いあい斬り (消費MP:28) ## Mass 0.016393 0.016393 ## ChiDist 5.431390 5.431390 ## Inertia 0.483607 0.483607 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 -0.112890 -0.112890 ## メッタ斬り (消費MP:36) まどろみ斬り (消費MP:38) ## Mass 0.016393 0.008197 ## ChiDist 5.431390 7.745967 ## Inertia 0.483607 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 -0.112890 1.025802 ## メッタメタ斬り (消費MP:41) 星天の守り (消費MP:48) ## Mass 0.008197 0.008197 ## ChiDist 7.745967 7.745967 ## Inertia 0.491803 0.491803 ## Dim. 1 7.745967 -0.129099 ## Dim. 2 0.000000 3.153807 ## 漆黒のツメ (消費MP:36) れんごく火球 (消費MP:27) ## Mass 0.016393 0.008197 ## ChiDist 5.431390 7.745967 ## Inertia 0.483607 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 -0.658755 -0.137507 ## 疾風迅雷 (消費MP:28) 白くかがやく光 (消費MP:110) ## Mass 0.008197 0.032787 ## ChiDist 7.745967 3.774917 ## Inertia 0.491803 0.467213 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 0.237590 0.237590 ## 真・よろいくだき (消費MP:40) 真・やいばくだき (消費MP:40) ## Mass 0.008197 0.008197 ## ChiDist 7.745967 7.745967 ## Inertia 0.491803 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 1.047088 -1.276665 ## いてつく眼光 (消費MP:21) 神速の剣技 (消費MP:36) 竜眼 (消費MP:48) ## Mass 0.008197 0.016393 0.008197 ## ChiDist 7.745967 5.431390 7.745967 ## Inertia 0.491803 0.483607 0.491803 ## Dim. 1 -0.129099 -0.129099 -0.129099 ## Dim. 2 -0.658755 1.025802 4.299633 ## 聖女のうた (消費MP:120) 聖魔斬 (消費MP:28) 蒼天魔斬 (消費MP:38) ## Mass 0.008197 0.008197 0.016393 ## ChiDist 7.745967 7.745967 5.431390 ## Inertia 0.491803 0.491803 0.483607 ## Dim. 1 -0.129099 -0.129099 -0.129099 ## Dim. 2 0.237590 3.153807 1.025802 ## 魔力かくせい (消費MP:16) 魔瘴弾 (消費MP:31) ## Mass 0.008197 0.008197 ## ChiDist 7.745967 7.745967 ## Inertia 0.491803 0.491803 ## Dim. 1 -0.129099 -0.129099 ## Dim. 2 -0.658755 0.755524 ## 黒くかがやく闇 (消費MP:124) ## Mass 0.008197 ## ChiDist 7.745967 ## Inertia 0.491803 ## Dim. 1 -0.129099 ## Dim. 2 0.237590
Correspondence analysis via skill - 3
print(ca_plot, "chart")
最後
謝謝大家(有機會到這一頁嗎XD)